SRPVS: A new motif searching algorithm for protein analysis

Xiaolu Huang, Hesham Ali, Anguraj Sadanandam, Rakesh Singh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

In some protein sequence regions, when two sequences share similar amino acid composition, they also share the same biological structure regardless of the sequence order. Traditional protein analysis tools, since they are sequence order dependent, cannot detect such a sequence order relaxing similarity. In this study, a more flexible protein comparison algorithm, the Similar enRiched Parikh Vector Searching (SRPVS) algorithm is designed to detect sequence similarity in a local-sequence-order-flexible manner. In SRPVS, a peptide sequence is broken into a group of Parikh vectors of predefined word sizes, and then Similar enRiched Parikh Vectors (SRPV) are searched between the two sequences and an Order Score is assigned to each pair of SRPV to reflect the order difference between the two sequences. A test has shown that SRPVS can detect shuffled protein sequence regions that share biological structure between two protein sequences.

Original languageEnglish (US)
Title of host publicationProceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004
Pages674-675
Number of pages2
StatePublished - 2004
EventProceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004 - Stanford, CA, United States
Duration: Aug 16 2004Aug 19 2004

Publication series

NameProceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004

Conference

ConferenceProceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004
Country/TerritoryUnited States
CityStanford, CA
Period8/16/048/19/04

ASJC Scopus subject areas

  • General Engineering

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